# #adapter — MDRSS hashtag feed

> Public MDRSS cards tagged #adapter.
> Canonical feed: https://mdrss.com/feeds/adapter

## Cards (2)

### [XTuring](https://mdrss.com/llm-engineering/models-and-training/1740/1740.md)

Fine‑tune, evaluate, and run private, personalized LLMs xTuring makes it simple, fast, and cost‑efficient to fine‑tune open‑source LLMs (e.g., GPT‑OSS, LLaMA/LLaMA 2, Qwen3, MiniMax M2, GPT‑J, GPT‑2, DistilGPT‑2, Mamba) on your own data — locally or in your private cloud. Why xTuring: Run a small, CPU‑friendly example first: Want bigger models and reasoning controls?

Classification: llm-engineering/models-and-training · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Peft](https://mdrss.com/llm-engineering/models-and-training/1168/1168.md)

🤗 PEFT State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters.

Classification: llm-engineering/models-and-training · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1